MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
In this course you will learn how to:
- Explain basic statistical measures and their application to real-life data sets
- Calculate and interpret measures of dispersion and explain deviations from a normal distribution
- Understand the use and appropriateness of different distributions
- Compare and contrast ways of visualizing data and create them using Python (no prior knowledge of Python necessary)
- Explain sampling theory and draw inferences about population parameters from sample statistics
- Formulate hypotheses on investment problems
Course 1 of 3 in the Data Science for Investment Professionals Specialization.
What You Will Learn
- Demonstrate the importance of and techniques for presenting data and the “data story”
- Understand data distributions and the importance and use of statistical measures
- Use statistical sampling and hypothesis testing to gain insight into population parameters
- Calculate data statistics and produce visualizations using Python
Syllabus
WEEK 1
Welcome to Data and Statistics Foundation for Investment Professionals
Measures of Central Tendency
WEEK 2
Measures of Dispersion
WEEK 3
Distributions
WEEK 4
Data Visualization Techniques
WEEK 5
Sampling Theory
WEEK 6
Hypothesis Testing
WEEK 7
Final Project
The final project places you in the role of a junior analyst who has been presented with data and needs to manipulate it in a meaningful way and present your findings to your manager in a well written report. It will test many of the things, including Python, that you have learned throughout this course. This final assessment is worth a maximum of 40% (out of a total of 100%) and counts towards your success in this course.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.